This example is one of many that I have been working on using the demo looking at maps of geomagnetic fields and field anomalies (amongst other things like topographic contour maps, solar activity, Goetian sigils etc). I'm an ambient/noise musician that is currently working on my first video installation based around this and other data transformed into music. I've been having trouble with saving though, after I finish tracing a map, HighC seems to save like normal but when I open the file up again a specific amount of the note data has been removed. I really don't know what is causing it. So I can really only submit the ones that are saved as 'complete'.

world geomagnetic model - epoch 2010 - main field declination:

http://www.mediafire.com/?dag3pc61gp4t43t

Internet Topology III - 939 node 2K-random HOT graph:

http://www.mediafire.com/?0f237xaado5o2lr

solar radio flux - geomagnetic index - 1959 to 2010

http://www.mediafire.com/?2kvbn50qtbg2sy1

I hope people enjoy the maps and the textures they generate. Personally, I find the geomagnetic model and anomaly maps the most interesting, as they tend to generate nice rich timbres. All the maps are hand edited over the maps brought in through the import background tool. I started playing around with HighC to try and hear the solar radio index patterns, as I have been developing a set of Python scripts so I can import SPIDR xml data and transform it into midi data for playing on external hardware and to write Csound files because I have been planning an album based around this data. Using the geographical locations of bases and data as a stratum for the rest of the work to structurally grow from. I've had to put this on hold as I was asked to do a video installation, but I've been loving HighC to help build textures for this task.

Very rich textures and sounds. I agree the geomagnetic model is the most interesting. Very xenakesque too. Early in the use of HighC, someone had generated sound files from stock data.

If you're proficient in scripting, for instance in the python language, it is very easy to generate HighC files from data: the file format is very close to JSON (only the class information is added to allow easy compression). To start finding out the format, just copy some sounds in HighC and paste them in a text editor. The sounds are represented as lists of points, with a given frequency in Hz and a time in seconds. The reverse works to: you can copy properly formatted text (tabs and line breaks are irrelevant, like in JSON) and paste it in HighC. You can also open .upic files with a text editor to find out more about the structure (formats of the envelopes, waveforms and patterns)....